Consumer electronic devices, such as desk-based and laptop computers, mobile phones, laptop computers, notebooks, tablets, MP3 players, connected TVs, etc., are ubiquitous. Part of the reason for the rapid growth in the number of mobile phones and other electronic devices is the rapid pace at which these devices evolve. More and more people are using multiple devices to access the internet. Through these devices they use browsers, apps or other methods to access content, interactive services and to communicate. Companies providing content can identify and track several user data points, such as the actual IP address, headers for webpage request and response, user's browsing history and various user device identifiers.
Typically, these user device identifiers are different across the various environments. In other words, one user may have many different user device identifiers also referred to herein as simply ‘UIDs’. These UIDs are not constructed to remain constant and they have a certain ‘lifespan’ from less than a second to weeks or months. There is a need to create applications capable of recognizing the user as one individual person across devices, websites and applications. This problem is most pressing in the online advertising industry, where various applications focused on providing information related to the reach and frequency of a digital campaign are unable to provide accurate advertising metrics, optimizations and measurements without a cross-device view of the user.